Questions:
Broad: What determines community structure in Lake Erie during the bloom season?
Specific:
Which environmental variables determine the composition of cyanobacterial taxa? Are there negative or positive correlations between different blooming genera?
Time series of cyanobacteria genus relative abundance
## Taxonomy Table: [14 taxa by 7 taxonomic ranks]:
## Kingdom Phylum Class Order
## Otu00005 "Bacteria" "Cyanobacteria" "Cyanobacteria" "SubsectionI"
## Otu00007 "Bacteria" "Cyanobacteria" "Cyanobacteria" "SubsectionI"
## Otu00037 "Bacteria" "Cyanobacteria" "Cyanobacteria" "SubsectionIII"
## Otu00044 "Bacteria" "Cyanobacteria" "Cyanobacteria" "SubsectionI"
## Otu00049 "Bacteria" "Cyanobacteria" "Cyanobacteria" "SubsectionI"
## Otu00063 "Bacteria" "Cyanobacteria" "Cyanobacteria" "SubsectionIV"
## Otu00147 "Bacteria" "Cyanobacteria" "Cyanobacteria" "SubsectionI"
## Otu00177 "Bacteria" "Cyanobacteria" "Cyanobacteria" "SubsectionI"
## Otu00193 "Bacteria" "Cyanobacteria" "Cyanobacteria" "SubsectionIV"
## Otu00304 "Bacteria" "Cyanobacteria" "Cyanobacteria" "SubsectionI"
## Otu00367 "Bacteria" "Cyanobacteria" "unclassified" "unclassified"
## Otu00403 "Bacteria" "Cyanobacteria" "Cyanobacteria" "SubsectionI"
## Otu00832 "Bacteria" "Cyanobacteria" "unclassified" "unclassified"
## Otu00903 "Bacteria" "Cyanobacteria" "Melainabacteria" "Obscuribacterales"
## Family Genus Species
## Otu00005 "FamilyI" "Microcystis" "Otu00005"
## Otu00007 "FamilyI" "Synechococcus" "Otu00007"
## Otu00037 "FamilyI" "Pseudanabaena" "Otu00037"
## Otu00044 "FamilyI" "Synechococcus" "Otu00044"
## Otu00049 "FamilyI" "unclassified" "Otu00049"
## Otu00063 "FamilyI" "Anabaena" "Otu00063"
## Otu00147 "FamilyI" "Synechococcus" "Otu00147"
## Otu00177 "FamilyI" "Synechococcus" "Otu00177"
## Otu00193 "FamilyI" "Anabaena" "Otu00193"
## Otu00304 "FamilyI" "unclassified" "Otu00304"
## Otu00367 "unclassified" "unclassified" "Otu00367"
## Otu00403 "FamilyI" "unclassified" "Otu00403"
## Otu00832 "unclassified" "unclassified" "Otu00832"
## Otu00903 "unclassified" "unclassified" "Otu00903"
This is weird . . .
cyanos %>%
subset_taxa(Class == "Cyanobacteria") -> cyanos
cyanos.otu <- t(otu_table(cyanos))
cyanos.melt <- psmelt(cyanos.otu)
For all correlation analyses, I removed low abundance OTUs (mean abundance < 0.0001 of total reads per sample i.e 1.5 ) which left a total of 399 heterotroph OTUs and 11 cyanobacteria OTUs.
These are spearman correlations with bonferroni correction between cyanobacterial OTUs
##
## Attaching package: 'psych'
##
## The following objects are masked from 'package:scales':
##
## alpha, rescale
##
## The following object is masked from 'package:ggplot2':
##
## %+%
| OTU1 | OTU2 | r | pvalue |
|---|---|---|---|
| Microcystis Otu00005 | Pseudanabaena Otu00037 | 0.7927082 | 0.0000000 |
| Pseudanabaena Otu00037 | Microcystis Otu00005 | 0.7927082 | 0.0000000 |
| Synechococcus Otu00177 | unclassified Otu00049 | 0.7754939 | 0.0000000 |
| unclassified Otu00049 | Synechococcus Otu00177 | 0.7754939 | 0.0000000 |
| Pseudanabaena Otu00037 | unclassified Otu00049 | 0.6800856 | 0.0000001 |
| unclassified Otu00049 | Pseudanabaena Otu00037 | 0.6800856 | 0.0000000 |
| Microcystis Otu00005 | unclassified Otu00049 | 0.6544720 | 0.0000004 |
| unclassified Otu00049 | Microcystis Otu00005 | 0.6544720 | 0.0000000 |
| Synechococcus Otu00007 | Synechococcus Otu00147 | 0.6180487 | 0.0000048 |
| Synechococcus Otu00147 | Synechococcus Otu00007 | 0.6180487 | 0.0000001 |
| Anabaena Otu00063 | Anabaena Otu00193 | 0.6092326 | 0.0000082 |
| Anabaena Otu00193 | Anabaena Otu00063 | 0.6092326 | 0.0000001 |
| Synechococcus Otu00044 | unclassified Otu00049 | 0.6071532 | 0.0000092 |
| unclassified Otu00049 | Synechococcus Otu00044 | 0.6071532 | 0.0000002 |
| unclassified Otu00049 | unclassified Otu00304 | 0.6059249 | 0.0000099 |
| unclassified Otu00304 | unclassified Otu00049 | 0.6059249 | 0.0000002 |
| Pseudanabaena Otu00037 | unclassified Otu00304 | 0.6017182 | 0.0000127 |
| unclassified Otu00304 | Pseudanabaena Otu00037 | 0.6017182 | 0.0000002 |
| Pseudanabaena Otu00037 | Synechococcus Otu00177 | 0.5765812 | 0.0000515 |
| Synechococcus Otu00177 | Pseudanabaena Otu00037 | 0.5765812 | 0.0000009 |
| Anabaena Otu00193 | Microcystis Otu00005 | 0.5328155 | 0.0000083 |
| Microcystis Otu00005 | Anabaena Otu00193 | 0.5328155 | 0.0004550 |
| Synechococcus Otu00007 | Synechococcus Otu00044 | 0.5206310 | 0.0007916 |
| Synechococcus Otu00044 | Synechococcus Otu00007 | 0.5206310 | 0.0000144 |
| Microcystis Otu00005 | unclassified Otu00304 | 0.5127862 | 0.0011183 |
| unclassified Otu00304 | Microcystis Otu00005 | 0.5127862 | 0.0000203 |
| Microcystis Otu00005 | Synechococcus Otu00177 | 0.5100565 | 0.0012586 |
| Synechococcus Otu00177 | Microcystis Otu00005 | 0.5100565 | 0.0000229 |
| unclassified Otu00049 | unclassified Otu00403 | 0.4837055 | 0.0037466 |
| unclassified Otu00403 | unclassified Otu00049 | 0.4837055 | 0.0000681 |
| Synechococcus Otu00177 | unclassified Otu00403 | 0.4786945 | 0.0045647 |
| unclassified Otu00403 | Synechococcus Otu00177 | 0.4786945 | 0.0000830 |
| Anabaena Otu00193 | unclassified Otu00049 | 0.4696079 | 0.0001178 |
| unclassified Otu00049 | Anabaena Otu00193 | 0.4696079 | 0.0064806 |
| Synechococcus Otu00177 | unclassified Otu00304 | 0.4419616 | 0.0177548 |
| unclassified Otu00304 | Synechococcus Otu00177 | 0.4419616 | 0.0003228 |
| unclassified Otu00304 | Anabaena Otu00193 | 0.3916358 | 0.0016453 |
| Anabaena Otu00193 | Synechococcus Otu00177 | 0.3893953 | 0.0017590 |
| Anabaena Otu00063 | Microcystis Otu00005 | 0.3837188 | 0.0020791 |
| unclassified Otu00403 | Microcystis Otu00005 | 0.3823983 | 0.0021606 |
| Synechococcus Otu00044 | Pseudanabaena Otu00037 | 0.3698081 | 0.0030938 |
| unclassified Otu00403 | Anabaena Otu00193 | 0.3695369 | 0.0031174 |
| unclassified Otu00403 | Synechococcus Otu00044 | 0.3646825 | 0.0035665 |
| Synechococcus Otu00177 | Synechococcus Otu00044 | 0.3598326 | 0.0040716 |
| Synechococcus Otu00044 | Microcystis Otu00005 | 0.3576298 | 0.0043212 |
| Synechococcus Otu00147 | Synechococcus Otu00044 | 0.3383701 | 0.0071462 |
| unclassified Otu00304 | Anabaena Otu00063 | 0.2995572 | 0.0180150 |
| unclassified Otu00049 | Synechococcus Otu00007 | 0.2504802 | 0.0495799 |
| unclassified Otu00403 | Synechococcus Otu00147 | -0.2539484 | 0.0464063 |
| Synechococcus Otu00147 | Anabaena Otu00063 | -0.3355312 | 0.0076766 |
| Anabaena Otu00193 | Synechococcus Otu00147 | -0.4324991 | 0.0004471 |
| Synechococcus Otu00147 | Anabaena Otu00193 | -0.4324991 | 0.0245915 |
Here we will examine correlations between cyanobacteria OTUs and heterotrophic OTUs in the full community
The number of positive associates is 71
The number of negative associates is 30
Genera represented by positive associates:
##
## Armatimonas Blastopirellula
## 0 1
## Candidatus_Aquiluna Candidatus_Captivus
## 0 1
## Candidatus_Methylacidiphilum Candidatus_Planktoluna
## 1 0
## Candidatus_Planktophila Candidatus_Protochlamydia
## 0 1
## Chthoniobacter CL500-29_marine_group
## 1 2
## Ferruginibacter Flavobacterium
## 0 1
## Fluviicola hgcI_clade
## 1 2
## Hyphomonas Inhella
## 1 1
## Lacibacter Limnobacter
## 2 1
## Limnohabitans Meganema
## 0 1
## MWH-UniP1_aquatic_group Novosphingobium
## 1 1
## OM27_clade Pedobacter
## 0 0
## Peredibacter Phenylobacterium
## 1 1
## Pirellula Planctomyces
## 4 2
## PRD01a011B Pseudarcicella
## 0 0
## Pseudospirillum Rhodobacter
## 0 1
## Roseiflexus Roseomonas
## 2 1
## Rubellimicrobium Sediminibacterium
## 1 1
## Solitalea Sphingorhabdus
## 0 0
## unclassified
## 38
Genera represented by negative associates:
##
## Armatimonas Blastopirellula
## 1 0
## Candidatus_Aquiluna Candidatus_Captivus
## 1 0
## Candidatus_Methylacidiphilum Candidatus_Planktoluna
## 0 1
## Candidatus_Planktophila Candidatus_Protochlamydia
## 1 0
## Chthoniobacter CL500-29_marine_group
## 0 3
## Ferruginibacter Flavobacterium
## 1 2
## Fluviicola hgcI_clade
## 1 1
## Hyphomonas Inhella
## 0 0
## Lacibacter Limnobacter
## 0 0
## Limnohabitans Meganema
## 1 0
## MWH-UniP1_aquatic_group Novosphingobium
## 0 0
## OM27_clade Pedobacter
## 1 1
## Peredibacter Phenylobacterium
## 0 0
## Pirellula Planctomyces
## 0 0
## PRD01a011B Pseudarcicella
## 1 1
## Pseudospirillum Rhodobacter
## 1 0
## Roseiflexus Roseomonas
## 0 0
## Rubellimicrobium Sediminibacterium
## 0 1
## Solitalea Sphingorhabdus
## 1 1
## unclassified
## 9
The number of positive associates is 21
The number of negative associates is 6
Genera represented by positive associates:
##
## Candidatus_Aquirestis Candidatus_Defluviella CL500-29_marine_group
## 0 1 1
## CL500-3 Flavisolibacter Flavobacterium
## 2 1 0
## Nitrospira Opitutus Terrimonas
## 0 1 1
## unclassified
## 14
Genera represented by negative associates:
##
## Candidatus_Aquirestis Candidatus_Defluviella CL500-29_marine_group
## 1 0 0
## CL500-3 Flavisolibacter Flavobacterium
## 0 0 1
## Nitrospira Opitutus Terrimonas
## 1 0 0
## unclassified
## 3
The number of positive associates is 96
The number of negative associates is 37
Genera represented by positive associates:
##
## Acidocella Arenimonas
## 1 0
## Armatimonas Bdellovibrio
## 0 1
## Blastopirellula Candidatus_Methylacidiphilum
## 1 2
## Candidatus_Planktophila Candidatus_Protochlamydia
## 0 1
## CL500-29_marine_group CL500-3
## 3 1
## Flavobacterium Fluviicola
## 4 2
## Gemmatimonas GKS98_freshwater_group
## 3 0
## hgcI_clade Hyphomonas
## 2 1
## Inhella Lacibacter
## 1 2
## LD28_freshwater_group Limnobacter
## 0 1
## Limnohabitans Meganema
## 0 1
## Novosphingobium OM27_clade
## 1 0
## Opitutus Peredibacter
## 0 1
## Phenylobacterium Pirellula
## 1 3
## Planctomyces Polynucleobacter
## 2 0
## Pseudarcicella Pseudospirillum
## 0 0
## Rhodobacter Roseiflexus
## 1 2
## Roseomonas Sediminibacterium
## 1 1
## Silanimonas SM1A02
## 1 1
## Solitalea Sphingorhabdus
## 0 0
## Terrimonas unclassified
## 1 53
Genera represented by negative associates:
##
## Acidocella Arenimonas
## 0 1
## Armatimonas Bdellovibrio
## 1 0
## Blastopirellula Candidatus_Methylacidiphilum
## 0 0
## Candidatus_Planktophila Candidatus_Protochlamydia
## 1 0
## CL500-29_marine_group CL500-3
## 4 0
## Flavobacterium Fluviicola
## 3 0
## Gemmatimonas GKS98_freshwater_group
## 0 1
## hgcI_clade Hyphomonas
## 2 0
## Inhella Lacibacter
## 0 0
## LD28_freshwater_group Limnobacter
## 1 0
## Limnohabitans Meganema
## 1 0
## Novosphingobium OM27_clade
## 0 2
## Opitutus Peredibacter
## 1 0
## Phenylobacterium Pirellula
## 0 0
## Planctomyces Polynucleobacter
## 0 1
## Pseudarcicella Pseudospirillum
## 1 2
## Rhodobacter Roseiflexus
## 0 0
## Roseomonas Sediminibacterium
## 0 1
## Silanimonas SM1A02
## 0 0
## Solitalea Sphingorhabdus
## 1 1
## Terrimonas unclassified
## 0 12
The number of positive associates is 16
The number of negative associates is 3
Genera represented by positive associates:
##
## Candidatus_Defluviella Candidatus_Methylacidiphilum
## 1 1
## CL500-29_marine_group CL500-3
## 0 2
## Flavobacterium Owenweeksia
## 1 0
## Phenylobacterium Roseospirillum
## 1 1
## Terrimonas unclassified
## 1 8
Genera represented by negative associates:
##
## Candidatus_Defluviella Candidatus_Methylacidiphilum
## 0 0
## CL500-29_marine_group CL500-3
## 1 0
## Flavobacterium Owenweeksia
## 0 1
## Phenylobacterium Roseospirillum
## 0 0
## Terrimonas unclassified
## 0 1
The number of positive associates is 71
The number of negative associates is 27
Genera represented by positive associates:
##
## Blastopirellula Candidatus_Methylacidiphilum
## 1 1
## Candidatus_Planktophila CL500-29_marine_group
## 0 2
## Flavobacterium Fluviicola
## 1 1
## GKS98_freshwater_group hgcI_clade
## 0 2
## Inhella Lacibacter
## 1 1
## Limnohabitans Meganema
## 0 1
## MWH-UniP1_aquatic_group Novosphingobium
## 1 1
## OM27_clade Pedobacter
## 0 0
## Peredibacter Phenylobacterium
## 1 1
## Pirellula Planctomyces
## 4 3
## Polynucleobacter Porphyrobacter
## 0 1
## Pseudarcicella Pseudospirillum
## 0 0
## Rhodobacter Roseiflexus
## 1 2
## Roseomonas Roseospirillum
## 1 1
## Rubellimicrobium Sediminibacterium
## 1 1
## SM1A02 Solitalea
## 1 0
## Sphingobium Sphingorhabdus
## 1 0
## unclassified
## 39
Genera represented by negative associates:
##
## Blastopirellula Candidatus_Methylacidiphilum
## 0 0
## Candidatus_Planktophila CL500-29_marine_group
## 1 2
## Flavobacterium Fluviicola
## 2 2
## GKS98_freshwater_group hgcI_clade
## 1 3
## Inhella Lacibacter
## 0 0
## Limnohabitans Meganema
## 1 0
## MWH-UniP1_aquatic_group Novosphingobium
## 0 0
## OM27_clade Pedobacter
## 1 1
## Peredibacter Phenylobacterium
## 0 0
## Pirellula Planctomyces
## 0 0
## Polynucleobacter Porphyrobacter
## 1 0
## Pseudarcicella Pseudospirillum
## 1 1
## Rhodobacter Roseiflexus
## 0 0
## Roseomonas Roseospirillum
## 0 0
## Rubellimicrobium Sediminibacterium
## 0 1
## SM1A02 Solitalea
## 0 1
## Sphingobium Sphingorhabdus
## 0 1
## unclassified
## 7
The number of positive associates is 6
The number of negative associates is 1
Genera represented by positive associates:
##
## Armatimonas Blastocatella Candidatus_Aquirestis
## 1 1 1
## Hirschia Planctomyces unclassified
## 1 1 1
Genera represented by negative associates:
##
## Armatimonas Blastocatella Candidatus_Aquirestis
## 0 0 0
## Hirschia Planctomyces unclassified
## 0 0 1
The number of positive associates is 40
The number of negative associates is 30
Genera represented by positive associates:
##
## Aeromonas Anaeromyxobacter
## 1 2
## BD1-7_clade Brevundimonas
## 0 0
## Candidatus_Aquirestis Candidatus_Methylacidiphilum
## 0 1
## CL500-29_marine_group CL500-3
## 3 2
## Flavisolibacter Flavobacterium
## 1 1
## Fluviicola hgcI_clade
## 1 1
## Hirschia Methylotenera
## 0 0
## OM27_clade Opitutus
## 0 1
## Pedobacter Planctomyces
## 1 0
## Roseiflexus Rubellimicrobium
## 1 0
## Sulfuritalea Terrimonas
## 0 1
## unclassified
## 23
Genera represented by negative associates:
##
## Aeromonas Anaeromyxobacter
## 0 0
## BD1-7_clade Brevundimonas
## 1 1
## Candidatus_Aquirestis Candidatus_Methylacidiphilum
## 1 0
## CL500-29_marine_group CL500-3
## 0 0
## Flavisolibacter Flavobacterium
## 0 1
## Fluviicola hgcI_clade
## 0 0
## Hirschia Methylotenera
## 1 1
## OM27_clade Opitutus
## 1 1
## Pedobacter Planctomyces
## 0 3
## Roseiflexus Rubellimicrobium
## 0 1
## Sulfuritalea Terrimonas
## 1 0
## unclassified
## 17
The number of positive associates is 78
The number of negative associates is 28
Genera represented by positive associates:
##
## Acidocella Anaeromyxobacter
## 1 0
## Armatimonas Blastocatella
## 0 1
## Blastopirellula Brevundimonas
## 1 1
## Candidatus_Methylacidiphilum Candidatus_Planktophila
## 1 0
## Chthoniobacter CL500-29_marine_group
## 1 1
## Flavobacterium Fluviicola
## 1 0
## Gemmatimonas GKS98_freshwater_group
## 1 0
## hgcI_clade Hirschia
## 2 1
## Hyphomonas Inhella
## 1 1
## LD28_freshwater_group Meganema
## 0 1
## MWH-UniP1_aquatic_group Pedobacter
## 1 0
## Phenylobacterium Pirellula
## 1 4
## Planctomyces Porphyrobacter
## 3 1
## Prosthecobacter Pseudarcicella
## 1 0
## Rhodobacter Roseiflexus
## 1 2
## Roseomonas Rubellimicrobium
## 1 1
## Sediminibacterium Solitalea
## 1 0
## Sphingobium Sphingorhabdus
## 1 0
## unclassified
## 45
Genera represented by negative associates:
##
## Acidocella Anaeromyxobacter
## 0 2
## Armatimonas Blastocatella
## 1 0
## Blastopirellula Brevundimonas
## 0 0
## Candidatus_Methylacidiphilum Candidatus_Planktophila
## 0 1
## Chthoniobacter CL500-29_marine_group
## 0 1
## Flavobacterium Fluviicola
## 1 3
## Gemmatimonas GKS98_freshwater_group
## 0 1
## hgcI_clade Hirschia
## 2 0
## Hyphomonas Inhella
## 0 0
## LD28_freshwater_group Meganema
## 1 0
## MWH-UniP1_aquatic_group Pedobacter
## 0 1
## Phenylobacterium Pirellula
## 0 0
## Planctomyces Porphyrobacter
## 0 0
## Prosthecobacter Pseudarcicella
## 0 1
## Rhodobacter Roseiflexus
## 0 0
## Roseomonas Rubellimicrobium
## 0 0
## Sediminibacterium Solitalea
## 1 1
## Sphingobium Sphingorhabdus
## 0 1
## unclassified
## 10
The number of positive associates is 19
The number of negative associates is 3
Genera represented by positive associates:
##
## Armatimonas Blastocatella Candidatus_Aquirestis
## 1 1 1
## Candidatus_Captivus Flavobacterium Hirschia
## 1 0 1
## Limnobacter MWH-UniP1_aquatic_group Pirellula
## 1 1 2
## Planctomyces Roseiflexus Rubellimicrobium
## 1 0 1
## unclassified
## 8
Genera represented by negative associates:
##
## Armatimonas Blastocatella Candidatus_Aquirestis
## 0 0 0
## Candidatus_Captivus Flavobacterium Hirschia
## 0 1 0
## Limnobacter MWH-UniP1_aquatic_group Pirellula
## 0 0 0
## Planctomyces Roseiflexus Rubellimicrobium
## 0 1 0
## unclassified
## 1
The number of positive associates is 81
The number of negative associates is 31
Genera represented by positive associates:
##
## Acidocella Algoriphagus Armatimonas
## 1 1 0
## Blastocatella Blastopirellula Candidatus_Planktophila
## 1 1 0
## Chthoniobacter CL500-29_marine_group Flavobacterium
## 1 2 1
## Fluviicola Gemmatimonas Haliscomenobacter
## 1 1 1
## hgcI_clade Hyphomonas Lacibacter
## 2 1 2
## Limnobacter Limnohabitans Meganema
## 1 0 1
## Methylorosula MWH-Ta3 Novosphingobium
## 0 0 1
## OM27_clade Owenweeksia Peredibacter
## 0 0 1
## Pirellula Planctomyces Polynucleobacter
## 2 3 0
## Pseudarcicella Rhodobacter Roseiflexus
## 0 1 2
## Roseomonas Rubellimicrobium Sediminibacterium
## 1 1 1
## Solitalea Sphingorhabdus unclassified
## 0 0 50
Genera represented by negative associates:
##
## Acidocella Algoriphagus Armatimonas
## 0 0 1
## Blastocatella Blastopirellula Candidatus_Planktophila
## 0 0 1
## Chthoniobacter CL500-29_marine_group Flavobacterium
## 0 2 2
## Fluviicola Gemmatimonas Haliscomenobacter
## 3 0 0
## hgcI_clade Hyphomonas Lacibacter
## 2 0 0
## Limnobacter Limnohabitans Meganema
## 0 1 0
## Methylorosula MWH-Ta3 Novosphingobium
## 1 1 0
## OM27_clade Owenweeksia Peredibacter
## 1 1 0
## Pirellula Planctomyces Polynucleobacter
## 0 0 1
## Pseudarcicella Rhodobacter Roseiflexus
## 1 0 2
## Roseomonas Rubellimicrobium Sediminibacterium
## 0 0 1
## Solitalea Sphingorhabdus unclassified
## 1 1 8
The number of positive associates is 2
The number of negative associates is 2
Genera represented by positive associates:
##
## Fluviicola Rubellimicrobium unclassified
## 0 1 1
Genera represented by negative associates:
##
## Fluviicola Rubellimicrobium unclassified
## 1 0 1
Here we will examine differences between heterotrophic associates in the colonial fractions for microcystis and synechococcus to see which heterotrophs are assoiated because they’re actually attaching to colonies
cyanos %>%
subset_taxa(Species == "Otu00005") %>%
psmelt() %>%
order_dates() -> cyanos.melt
ggplot(cyanos.melt, aes(x = Date, y = Abundance, group = Station, color = Station)) +
geom_point() +
geom_line() +
stackbar_theme
The number of positive associates is 6
The number of negative associates is 5
Genera represented by positive associates:
##
## Flavobacterium hgcI_clade Limnohabitans Phenylobacterium
## 0 0 0 1
## Polynucleobacter Rhodobacter unclassified
## 0 1 4
Genera represented by negative associates:
##
## Flavobacterium hgcI_clade Limnohabitans Phenylobacterium
## 1 1 1 0
## Polynucleobacter Rhodobacter unclassified
## 1 0 1
cyanos %>%
subset_taxa(Species == "Otu00007") %>%
psmelt() %>%
order_dates() -> cyanos.melt
ggplot(cyanos.melt, aes(x = Date, y = Abundance, group = Station, color = Station)) +
geom_point() +
geom_line() +
stackbar_theme
The number of positive associates is 3
The number of negative associates is 0
Genera represented by positive associates:
##
## CL500-29_marine_group hgcI_clade Terrimonas
## 1 1 1
Genera represented by negative associates:
##
## CL500-29_marine_group hgcI_clade Terrimonas
## 0 0 0
cyanos %>%
subset_taxa(Species == "Otu00044") %>%
psmelt() %>%
order_dates() -> cyanos.melt
ggplot(cyanos.melt, aes(x = Date, y = Abundance, group = Station, color = Station)) +
geom_point() +
geom_line() +
stackbar_theme
The number of positive associates is 0
The number of negative associates is 0
Genera represented by positive associates:
## < table of extent 0 >
Genera represented by negative associates:
## < table of extent 0 >
cyanos %>%
subset_taxa(Species == "Otu00005") %>%
psmelt() %>%
order_dates() -> cyanos.melt
ggplot(cyanos.melt, aes(x = Date, y = Abundance, group = Station, color = Station)) +
geom_point() +
geom_line() +
stackbar_theme
The number of positive associates is 24
The number of negative associates is 4
Genera represented by positive associates:
##
## Blastopirellula Candidatus_Planktoluna Flavobacterium
## 1 0 0
## hgcI_clade Meganema Phenylobacterium
## 1 1 1
## Pirellula Rhodobacter Roseomonas
## 1 1 1
## unclassified Veillonella
## 17 0
Genera represented by negative associates:
##
## Blastopirellula Candidatus_Planktoluna Flavobacterium
## 0 1 1
## hgcI_clade Meganema Phenylobacterium
## 0 0 0
## Pirellula Rhodobacter Roseomonas
## 0 0 0
## unclassified Veillonella
## 1 1
cyanos %>%
subset_taxa(Species == "Otu00007") %>%
psmelt() %>%
order_dates() -> cyanos.melt
ggplot(cyanos.melt, aes(x = Date, y = Abundance, group = Station, color = Station)) +
geom_point() +
geom_line() +
stackbar_theme
The number of positive associates is 1
The number of negative associates is 0
Genera represented by positive associates:
##
## unclassified
## 1
Genera represented by negative associates:
##
## unclassified
## 0
cyanos %>%
subset_taxa(Species == "Otu00044") %>%
psmelt() %>%
order_dates() -> cyanos.melt
ggplot(cyanos.melt, aes(x = Date, y = Abundance, group = Station, color = Station)) +
geom_point() +
geom_line() +
stackbar_theme
The number of positive associates is 2
The number of negative associates is 0
Genera represented by positive associates:
##
## Roseomonas Roseospirillum
## 1 1
Genera represented by negative associates:
##
## Roseomonas Roseospirillum
## 0 0
b <- bioenv(bray.sub, env, method = "spearman", trace = T, upto = 12)
## 4095 possible subsets (this may take time...)
## No. of variables 1, No. of sets 12... done (0.3%)
## No. of variables 2, No. of sets 66... done (1.9%)
## No. of variables 3, No. of sets 220... done (7.3%)
## No. of variables 4, No. of sets 495... done (19.4%)
## No. of variables 5, No. of sets 792... done (38.7%)
## No. of variables 6, No. of sets 924... done (61.3%)
## No. of variables 7, No. of sets 792... done (80.6%)
## No. of variables 8, No. of sets 495... done (92.7%)
## No. of variables 9, No. of sets 220... done (98.1%)
## No. of variables 10, No. of sets 66... done (99.7%)
## No. of variables 11, No. of sets 12... done (100%)
## No. of variables 12, No. of sets 1... done (100%)
summary(b)
## size
## Turbidity 1
## Temp Turbidity 2
## pH Temp Turbidity 3
## pH Temp Turbidity Chla 4
## pH Secchi Temp Turbidity Nitrate 5
## pH Temp Turbidity SRP Nitrate ParMC 6
## pH Secchi Temp Turbidity SRP Nitrate ParMC 7
## pH Secchi Temp Turbidity SRP Nitrate Chla ParMC 8
## pH Secchi Temp Turbidity SRP Nitrate Chla ParMC Phycocyanin 9
## pH Secchi Temp Turbidity SRP Nitrate Ammonia Chla ParMC Phycocyanin 10
## pH Secchi Temp Turbidity SRP POC Nitrate Ammonia Chla ParMC Phycocyanin 11
## pH Secchi Temp Turbidity SRP POC Nitrate Ammonia H2O2 Chla ParMC Phycocyanin 12
## correlation
## Turbidity 0.4355
## Temp Turbidity 0.4798
## pH Temp Turbidity 0.5048
## pH Temp Turbidity Chla 0.5002
## pH Secchi Temp Turbidity Nitrate 0.4909
## pH Temp Turbidity SRP Nitrate ParMC 0.4840
## pH Secchi Temp Turbidity SRP Nitrate ParMC 0.4759
## pH Secchi Temp Turbidity SRP Nitrate Chla ParMC 0.4642
## pH Secchi Temp Turbidity SRP Nitrate Chla ParMC Phycocyanin 0.4461
## pH Secchi Temp Turbidity SRP Nitrate Ammonia Chla ParMC Phycocyanin 0.4245
## pH Secchi Temp Turbidity SRP POC Nitrate Ammonia Chla ParMC Phycocyanin 0.3790
## pH Secchi Temp Turbidity SRP POC Nitrate Ammonia H2O2 Chla ParMC Phycocyanin 0.3104
# Select best variables from env
env %>%
select(pH, Temp, Turbidity) -> env.subset
# Scale env variables and calculate euclidean distance
env.scale <- scale(env.subset)
env.dist <- dist(env.scale, method = "euclidean")
# Run partial mantel
mantel(bray.sub, env.dist, method = "spearman")
##
## Mantel statistic based on Spearman's rank correlation rho
##
## Call:
## mantel(xdis = bray.sub, ydis = env.dist, method = "spearman")
##
## Mantel statistic r: 0.5048
## Significance: 0.001
##
## Upper quantiles of permutations (null model):
## 90% 95% 97.5% 99%
## 0.0818 0.1100 0.1351 0.1727
## Permutation: free
## Number of permutations: 999
Here we will construct a regression tree with phototroph abundance as reponse and environmental conditions as predictors to understand the bottom up conditions that determine community of phototrophs
. . . in progress